Privacy Preservation Quality of Service Model for Data Exposure

Mobile applications and smartphones are closely related to each other. Mobile application plays a crucial role among smartphone users. It has gained enormous support from the smartphone users ranging from young to elder generations. It is very common to download and install desired mobile applicatio...

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Bibliographic Details
Published in:Procedia computer science 2019, Vol.161, p.1139-1146
Main Authors: Bakar, Anizah Abu, Singh, Manmeet Mahinderjit, Mohd Shariff, Azizul Rahman
Format: Article
Language:English
Subjects:
Mobile Application
Privacy Risk Score
Residual Risk
Sensitive Data Risk
Sensor
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Summary:Mobile applications and smartphones are closely related to each other. Mobile application plays a crucial role among smartphone users. It has gained enormous support from the smartphone users ranging from young to elder generations. It is very common to download and install desired mobile applications from application store to aid in completing particular tasks with ease. However, this behavior exposes user towards privacy risk as it has become a concern in smartphone usage. In this research, we propose a mathematical model named Privacy Risk Model (PRiMo) that measures the risk score of a user in smartphone usage. We are approaching the privacy issues in mobile applications from the individual’s perspective. We conduct studies on different categories of mobile applications to determine the risk posed by the mobile applications. There is no standardization for residual risk. Therefore, by using the proposed model, we are exploring and creating a standardization for residual risk that becomes a benchmark for user to accept and live with that risk.
ISSN:1877-0509
1877-0509
DOI:10.1016/j.procs.2019.11.226